occurrence and distribution of nitrate and pesticides in bowdle aquifer, south dakota

A shallow aquifer in central South Dakota was monitored for thepresence of nitrate and pesticides. A total of 593 nitrate samples and428 pesticide samples were analyzed from nine different sites and 14wells between 1989 and 1994. Nested wells were installed at four sitesto characterize the distribution pattern of nitrate and pesticidemovement in ground water. Nitrate concentrations and pesticidedetections were qualitatively compared with area precipitation and watertable fluctuations. The results indicate that nitrates tend to betransported by a leaching mechanism in a matrix flow and may appearin ground water within months after the fertilizer application in thefields. The pesticide movement is primarily controlled by geologicaland chemical characteristics of medium and pesticides.     

An analytical model for the assessment of pesticide exposure levels in soils and groundwater

The movement and degradation of pesticide residues in soils and groundwater are complex processes affected by soil physical, (bio)chemical, and hydrogeological properties, climatic conditions, and agricultural practices. This work presents a physically-based analytical model suitable for long-term predictions of pesticide concentrations in groundwater. The primary interest is to investigate the impact of soil environment, related physical and (bio)chemical processes, especially, volatilization, crop uptake, and agricultural practices on long-term vulnerability of groundwater to contamination by pesticides. The soil is separated into root and intermediate vadose zones, each with uniform properties. Transport in each soil zone is modeled on the basis of complete mixing, by spatial averaging the related point multiphase-transport partial differential equation (i.e., linear-reservoir models). Transport in the aquifer, however, is modeled by a two-dimensional advection-dispersion transport equation, considering adsorption and first-order decay rate. Vaporization in the soil is accounted for by assuming liquid-vapor phase partitioning using Henry's law, and vapor flux (volatilization) from the soil surface is modeled by diffusion through an air boundary layer. Sorption of liquid-phase solutes by crops is described by a linear relationship which is valid for first-order (passive) crop uptake. The model is applied to five pesticides (atrazine, bromacil, chlordane, heptachlor, and lindane), and the potential for pesticide contamination of groundwater is investigated for sandy and clayey soils. Simulation results show that groundwater contamination can be substantially reduced for clayey soil environments, where bio(chemical) degradation and volatilization are most efficient as natural loss pathways for the pesticides. Also, uptake by cross can be a significant mechanism for attenuating exposure levels in ground-water especially in a sandy soil environment, and for relatively persisting pesticides. Further, simulations indicate that changing agricultural practices can have a profound effect on vulnerability of groundwater to mobile and relatively persisting pesticides.     

Ground water discharge and the related nutrient and trace metal fluxes into Quincy bay,Massachusetts

Measurement of the rate and direction of ground water flow beneath Wollaston Beach, Quincy, Massachusetts by use of a heat-pulsing flowmeter shows a mean velocity in the bulk sediment of 40 cm d^–1. The estimated total discharge of ground water into Quincy Bay during October 1990 was 1324–2177 m³ d^–1, a relatively low ground water discharge rate. The tides have only a moderate effect on the rate and direction of this flow. Other important controls on the rate and volume of ground water flow are the limited thickness, geographic extent, and permeability of the aquifer. Comparisons of published streamflow data and estimates of ground water discharge indicate that ground water makes up between 7.4–12.1% of the gaged freshwater input into Quincy Bay. The data from this study suggest the ground water discharge is a less important recharge component to Quincy Bay than predicted by National Urban Runoff Program (NURP) models.The high nitrate and low nitrite and ammonia concentrations in the ground water at the backshore well sites and low nitrate and high nitrite and ammonia concentrations in the water flowing from the foreshore suggests that denitrification is active in the sediments. The low ground water flow rates and low nitrate concentrations in the foreshore samples suggest that little or no nitrate is surviving the denitrification process to affect the planktonic community. Similarly, oxidizing conditions in the aquifer and low trace metal concentrations in the ground water samples suggest that the metals may be precipitating and binding to sedimentary phases before impacting the bay.     

Simulating Nitrate Leaching Profiles in a Highly Permeable Vadose Zone

An approach is developed to simulate leaching of a dissolved chemical constituent in the vadose zone of an aquifer. Specifically, nitrate loading at the water table for different water table depths, for a range of aquifer permeability values, and for different cases of heterogeneity of the aquifer, are considered. Models from the literature are first used to derive soil–water characteristic curves (water retention and hydraulic conductivity) from a grain size distribution curve for unsaturated conditions. Given infiltration from the surface, the initial conditions for the chemical concentration, and the water content profile, leaching of the chemical in the vadose zone is simulated as a function of both time and depth. The methodology is illustrated for a permeable aquifer. Simulations are undertaken using a finite element code for saturated and unsaturated flow. Different scenarios are simulated depending on the heterogeneity of the aquifer and the depth of the water table. Modeling results show that in the example case studied, nitrate concentration loading at the water table does not depend strongly on the position of the water table, but rather on the material properties of the aquifer. The contribution of this endeavor resides in the methodology which allows a prediction of nitrate leaching using only the grain size property of the aquifer. It allows practitioners to obtain a first assessment of leaching with limited data.     

Exploring the Relationship Between Hydrologic Parameters and Nutrient Loads Using Digital Elevation Model and GIS – A Case Study from Sugarcreek Headwaters, Ohio, U.S.A.

Ohio is typical among the Midwestern and Eastern United States with high levels of water pollutants, the main sources being from agriculture. In this study, we used a digital elevation model in conjunction with hydrological indices to determine the role of landscape complexity affecting the spatial and temporal variation in pollutant levels, in one of the most impaired headwater streams in Ohio. More than eighty five percent of the study area is dominated by agriculture. Spatial distribution of slope (S), altitude and wetness index along with other watershed parameters such as flow direction, flow accumulation, stream networks, flow stream orders and erosion index were used within a Geographic Information Systems framework to quantify variation in nitrate and phosphate loads to headwater streams. Stream monitoring data for nutrient loads were used to correlate the observed spatial and temporal patterns with hydrological parameters using multiple linear regressions. Results from the wetness index calculated from a digital elevation model suggested a range of 0.10–16.39, with more than 35% having values less than 4.0. A Revised Universal Soil Loss Equation (RUSLE) predicted soil loss in the range of 0.01–4.0 t/ha/yr. Nitrate nitrogen levels in the study area paralleled precipitation patterns over time, with higher nitrate levels corresponding to high precipitation. Atmospheric deposition through precipitation could explain approximately 35% of total nitrate levels observed in streams. Among the different topographic variables and hydrological indices, results from the step-wise multiple regression suggested the following best predictors, (1) elevation range and upstream flow length for nitrate, (2) flow direction and upstream flow length for ammonia-nitrogen and slope, and (3) elevation range for phosphate levels. Differences in the landscape models observed for nitrate, phosphate and ammonia-nitrogen in the surface waters were attributed partly to differences in the chemical activity and source strengths of the different forms of these nutrients through agricultural management practices. The results identify geomorphologic and landscape characteristics that influence pollutant levels in the study area.     

Use of cluster and principal component analyses to profile areas in California where ground water has been contaminated by pesticides

An empirical approach to profiling areas of ground water contamination by pesticides was devised that did not rely upon determining the level of vulnerability between land areas and that did not assume any particular pathway for ground water contamination. Climatic and soil data were obtained for 1-square mile sections of land in California where pesticide residues had been found in well water samples and the detection was attributed to legal agricultural applications. These sections were designated as known contaminated (KC) sections. Climate and soil data were also obtained for sections which lacked either well sampling data or a positive pesticide detection. These sections were designated as candidate sections. Statistical procedures were used to cluster groups of KC sections first with respect to climate characteristics and then with respect to soil characteristics. Principal components analysis (PCA) was used to construct a statistical profile of soil variables for each cluster of KC sections. A method based on the PCA was developed to compare the similarity of soil profiles derived for each KC section cluster to individual candidate sections. Since the profiling scheme was based only on data from KC sections, candidate sections that did not match any KC cluster profile could only be considered dissimilar to contaminated sections, receiving a status of not-classified. This profiling method is flexible and it can be revised to incorporate updated well sampling information.     

Application of drastic model and GIS: for assessing vulnerability in hard rock granitic aquifer

Geographic information system (GIS) has become one of the leading tools in the field of hydrogeological science that helps in assessing, monitoring, and conserving groundwater resources. Groundwater is a finite resource, which is being overexploited due to increase in demand over the years leading to decrease in its potentiality. In the present study, DRASTIC model has been used to prepare groundwater vulnerable zone in hard rock aquifer of granitic terrain. The main objective is to determine susceptible zone for groundwater pollution by integrating hydrogeological layers in GIS environment. The layers such as depth of aquifer, recharge, aquifer yield, soil type, topography, vadose zone, and transmissivity are incorporated in the DRASTIC model. The final output of the map shows that around 60% of the area falls under low to no risk of pollution zone. The high risk of pollution zones are mostly present towards the margin of southeastern periphery. The lower part of the basin as well as small area on northern side falls under moderate risk of pollution zone. For the assessment of groundwater pollution zone, 24 groundwater samples have been collected from different vulnerable zones. The chemical analysis of sample shows that the southeastern margin of basin has relatively high concentration of nitrate as compared to other parts of the basin. It is present in high pollution zone as well as moderate pollution zone. The present model can be used for assessment and management of groundwater.     

Groundwater vulnerability assessment using DRASTIC and Pesticide DRASTIC models in intense agriculture area of the Gangetic plains,India

Delineating areas susceptible to contamination from anthropogenic sources form an important component of sustainable management of groundwater resources. The present research aims at estimating vulnerability of groundwater by application of DRASTIC and Pesticide DRASTIC models in the southern part of the Gangetic plains in the state of Bihar. The DRASTIC and Pesticide DRASTIC models have considered seven parameters viz. depth to water level, net recharge, aquifer material, soil material, topography, impact of vadose zone and hydraulic conductivity. A third model, Pesticide DRASTIC LU has been adopted by adding land use as an additional parameter, to assess its impact on vulnerability zonation. The DRASTIC model indicated two vulnerable categories, moderate and high, while the Pesticide DRASTIC model revealed moderate, high and very high vulnerable categories. Out of the parameters used, depth to water level affected the vulnerability most. The parameter caused least impact was topography in DRASTIC, while in case of Pesticide DRASTIC and Pesticide DRASTIC LU models, the parameter was hydraulic conductivity. A linear regression between groundwater NO₃ concentrations and the vulnerability zonation revealed better correlation for Pesticide DRASTIC model, emphasising the effectiveness of the model in assessing groundwater vulnerability in the study region. Considering all three models, the most vulnerable areas were found to be concentrated mainly in two zones, (i) in the south-western part along Ekangarsarai-Islampur patch and (ii) around Biharsharif-Nagarnausa area in the central part. Both zones were characterised by intensive vegetable cultivation with urban areas in between.     

Probability-based nitrate contamination map of groundwater in Kinmen

Groundwater supplies over 50 % of drinking water in Kinmen. Approximately 16.8 % of groundwater samples in Kinmen exceed the drinking water quality standard (DWQS) of NO₃ ^?-N (10 mg/L). The residents drinking high nitrate-polluted groundwater pose a potential risk to health. To formulate effective water quality management plan and assure a safe drinking water in Kinmen, the detailed spatial distribution of nitrate–N in groundwater is a prerequisite. The aim of this study is to develop an efficient scheme for evaluating spatial distribution of nitrate–N in residential well water using logistic regression (LR) model. A probability-based nitrate–N contamination map in Kinmen is constructed. The LR model predicted the binary occurrence probability of groundwater nitrate–N concentrations exceeding DWQS by simple measurement variables as independent variables, including sampling season, soil type, water table depth, pH, EC, DO, and Eh. The analyzed results reveal that three statistically significant explanatory variables, soil type, pH, and EC, are selected for the forward stepwise LR analysis. The total ratio of correct classification reaches 92.7 %. The highest probability of nitrate–N contamination map presents in the central zone, indicating that groundwater in the central zone should not be used for drinking purposes. Furthermore, a handy EC–pH-probability curve of nitrate–N exceeding the threshold of DWQS was developed. This curve can be used for preliminary screening of nitrate–N contamination in Kinmen groundwater. This study recommended that the local agency should implement the best management practice strategies to control nonpoint nitrogen sources and carry out a systematic monitoring of groundwater quality in residential wells of the high nitrate–N contamination zones.     

A multi criteria analog model for assessing the vulnerability of rural catchments to road spills of hazardous substances

Road spills of hazardous substances are common in developing countries due to increasing industrialization and traffic accidents, and represent a serious threat to soils and water in catchments. There is abundant literature on equations describing the wash-off of pollutants from roads during a storm event and there are a number of watershed models incorporating those equations in storm water quality algorithms that route runoff and pollution yields through a drainage system towards the catchment outlet. However, methods describing catchment vulnerability to contamination by road spills based solely on biophysical parameters are scarce. These methods could be particularly attractive to managers because they can operate with a limited amount of easily collectable data, while still being able to provide important insights on the areas more prone to contamination within the studied watershed. The purpose of this paper was then to contribute with a new vulnerability model. To accomplish the goal, a selection of medium properties appearing in wash-off equations and routing algorithms were assembled and processed in a parametric framework based on multi criteria analysis to define the watershed vulnerability. However, parameters had to be adapted because wash-off equations and water quality models have been developed to operate primarily in the urban environment while the vulnerability model is meant to run in rural watersheds. The selected parameters were hillside slope, ground roughness (depending on land use), soil permeability (depending on soil type), distance to water courses and stream density. The vulnerability model is a spatially distributed algorithm that was prepared to run under the IDRISI Selva software, a GIS platform capable of handling spatial and alphanumeric data and execute the necessary terrain model, hydrographic and thematic analyses. For illustrative purposes, the vulnerability model was applied to the legally protected Environmental Protection Area (APA), located in the Uberaba region, state of Minas Gerais, Brazil. In this region, the risk of accidents causing chemical spills is preoccupying because large quantities of dangerous materials are transported in two important distribution highways while the APA is fundamental for the protection of water resources, the riverine ecosystems and remnants of native vegetation. In some tested scenarios, model results show 60% of vulnerable areas within the studied area. The most sensitive parameter to vulnerability is soil type. To prevent soils from contamination, specific measures were proposed involving minimization of land use conflicts that would presumably raise the soil's organic matter and in the sequel restore the soil's structural functions. Additionally, the present study proposed the preservation and reinforcement of riparian forests as one measure to protect the quality of surface water.     

Assessment of groundwater vulnerability in the coastal region of Oman using DRASTIC index method in GIS environment

A study was carried out to develop a vulnerability map for Barka region in the North Batina of Oman using DRASTIC vulnerability index method in GIS environment. DRASTIC layers were created using data from published reports and the seven DRASTIC layers were processed by the ArcGIS geographic information system. Finally, DRASTIC maps were created for 1995 and 2004 to understand the long-term changes in the vulnerability index. DRASTIC vulnerability maps were evaluated using groundwater quality data such as chemical and biological parameters. DRASTIC vulnerability maps of 1995 and 2004 indicate that the northern part of Barka is more vulnerable to pollution than southern part and the central part of Barka also shows high relative vulnerability which is mostly related to the high conductivity values. Moreover, the changes in water level due to high abstraction rate of groundwater reflect in the vulnerability maps and low vulnerability area is increased in the southern part during 2004 compared to 1995. Moreover, regional distribution maps of nitrate, chloride and total and fecal coliforms are well correlated with DRASTIC vulnerability maps. In contrast to this, even though DRASTIC method predicted the central part of the study region is highly vulnerable, both chemical and biological parameters show lower concentrations in this region compared to coastal belt, which is mainly due to agricultural and urban development. In Barka, urban development and agricultural activities are very high in coastal region compared to southern and central part of the study area. Hence, this study concluded that DRASTIC method is also applicable in coastal region having ubiquitous contamination sources.     

profiling areas of ground water contamination by pesticides in california: phase ii – evaluation and modification of a statistical model

A well sampling study was conducted to evaluate anempirical approach to classifying areasof land in California as vulnerable to ground watercontamination by pesticides (Troiano et al., 1994). Wells were sampled from sections of land that had noprevious detections of pesticideresidues. The sections had been classified into vulnerablesoil clusters or into a not-classified groupusing a procedure based on Principal Components Analysis(PCA). Grape, citrus, and olive growingareas of Fresno and Tulare Counties were targeted, areas wherepre-emergence herbicide residues hadbeen detected in well water. Overall, herbicide residues weredetected in 75 of 176 sampled wells, ahigh frequency of detection in relation to results fromprevious targeted well sampling studies. Sinceresidues were also detected in the not-classified group, theclassification procedure was modified usingan approach based on Canonical Variates Analysis (CVA). Moresections were classified intovulnerable soil clusters with the CVA approach than with thePCA method. Data from two otherexplanatory variables, depth to ground water and amount ofpesticide used per section, were includedto illustrate how additional information can be incorporatedinto this approach of identifying vulnerable areas.     

Monitoring of the three organophosphate esters TBP,TCEP and TBEP in river water and ground water (Oder,Germany)

The behaviour of the three organophosphate esters tributyl phosphate (TBP), tris(2-chloroethyl)phosphate (TCEP) and tris(2-butoxyethyl)phosphate (TBEP) during infiltration of river water to ground water has been investigated. The monitoring site is the Oder River and the adjacent Oderbruch aquifer. From March 2000 to July 2001, 76 ground water samples from monitoring wells located close to the Oder River and nine river water samples were collected. Additionally, influent and effluent samples from local waste water treatment plants, one sample of rain water and samples of roof runoff were collected. All samples were analysed by solid-phase-extraction followed by gas chromatography/mass spectrometry. TBP, TCEP and TBEP were detected at mean values of 622 ng l(-1), 352 ng l(-1), and 2955 ng l(-1), respectively in municipal waste water effluents. This points to a major input of these compounds into the Oder River by municipal waste water discharge. The concentrations of TBP and TBEP decreased downstream the Oder River possibly due to aerobic degradation. TBP, TCEP and TBEP were detected in ground water influenced predominantly by bank-filtered water. This demonstrates a transport of organic compounds by river water infiltration to ground water. TBP, TCEP and TBEP were also detected in rain water precipitation, roof runoff and ground water predominantly influenced by rain water infiltration. This hints to an input of these compounds to ground water by dry and wet deposition after atmospheric transport. Organophosphate esters were also detected in parts of the aquifer at 21 m depth. This demonstrates low anaerobic degradation rates of TBP, TCEP and TBEP.     

Total petroleum hydrocarbon distribution in soils and groundwater in Songyuan oilfield, Northeast China

In order to investigate the distribution of the total petroleum hydrocarbons (TPH) in groundwater and soil, a total of 71 groundwater samples (26 unconfined groundwater samples, 37 confined groundwater samples, and 8 deeper confined groundwater samples) and 80 soil samples were collected in the Songyuan oilfield, Northeast China, and the vertical variation and spatial variability of TPH in groundwater and soil were assessed. For the groundwater from the unconfined aquifer, petroleum hydrocarbons were not detected in three samples, and for the other 23 samples, concentrations were in the range 0.01–1.74 mg/l. In the groundwater from the confined aquifer, petroleum hydrocarbons were not detected in two samples, and in the other 35 samples, the concentrations were 0.04–0.82 mg/l. The TPH concentration in unconfined aquifer may be influenced by polluted surface water and polluted soil; for confined aquifer, the injection wells leakage and left open hole wells may be mainly responsible for the pollution. For soils, the concentrations of TPH varied with sampling depth and were 0–15 cm (average concentration, 0.63 mg/g), >40–55 cm (average concentration, 0.36 mg/g), >100–115 cm (average concentration, 0.29 mg/g), and >500–515 cm (average concentration, 0.26 mg/g). The results showed that oil spillage and losses were possibly the main sources of TPH in soil. The consequences concluded here suggested that counter measures such as remediation and long-term monitoring should be commenced in the near future, and effective measures should be taken to assure that the oilfields area would not be a threat to human health.     

Sub-Surface Investigations on Deep Saline Groundwater of Charnockite Rock Formation, Kalpakkam, India

Investigations on geohydrological aspects of coastal aquifer are important in order to understand the mechanism of ground water salinisation. The present study describes the salinity variations of ground water in deep boreholes drilled in Charnockite rock formation of Kalpakkam, on the eastern coast of India. Water samples collected up to 600m depth were analyzed for salinity variation. It is noticed that in one of the boreholes, (borehole K1), the salinity level is found to be 74 parts per thousand (ppt) at 400 m depth. Influence of surface saline water bodies viz., sea (26-28.5 ppt), backwaters (27-30 pt) and Buckingham canal (27-32 ppt) as the possible sources of recharge of fresh waters through joint and fracture system of the rock are discussed in this paper. Studies would assist in understanding the geohydrological characteristics of deep geological formation.     

Evaluation Of Ground Water Quality In Dakhla Oasis (Egyptian Western Desert)

Chemical analyses of ground water and soil samples at Zakhera Village (Dakhla Oasis, Egyptian Western Desert) were carried out on ten artesian wells. The interrelationships between the major and minor ions' behaviour and the prevailing geological and environmental conditions were examined. Ground water quality varies widely, even at short distances, depending on hydrogeological conditions, pumping period, depth of aquifer, type of soil, and human activities. Significant differences of the flux coefficient values for metals and non-metals were observed as a result of the redox status of their environment and adsorption phenomena. Water quality index (WQI), and saturation index (SI) indicated the suitability of these samples for different uses.     

Using GA-Ridge regression to select hydro-geological parameters influencing groundwater pollution vulnerability

For groundwater conservation and management, it is important to accurately assess groundwater pollution vulnerability. This study proposed an integrated model using ridge regression and a genetic algorithm (GA) to effectively select the major hydro-geological parameters influencing groundwater pollution vulnerability in an aquifer. The GA-Ridge regression method determined that depth to water, net recharge, topography, and the impact of vadose zone media were the hydro-geological parameters that influenced trichloroethene pollution vulnerability in a Korean aquifer. When using these selected hydro-geological parameters, the accuracy was improved for various statistical nonlinear and artificial intelligence (AI) techniques, such as multinomial logistic regression, decision trees, artificial neural networks, and case-based reasoning. These results provide a proof of concept that the GA-Ridge regression is effective at determining influential hydro-geological parameters for the pollution vulnerability of an aquifer, and in turn, improves the AI performance in assessing groundwater pollution vulnerability.     

Evaluation of hydrochemical changes due to intensive aquifer exploitation: case studies from Mexico

The impact of intensive aquifer exploitation has been observed in numerous places around the world. Mexico is a representative example of this problem. In 2010, 101 out of the 653 aquifers recognized in the country, showed negative social, economic, and environmental effects related to intensive exploitation. The environmental effects include, among others, groundwater level decline, subsidence, attenuation, and drying up of springs, decreased river flow, and deterioration of water quality. This study aimed at determining the hydrochemical changes produced by intensive aquifer exploitation and highlighting water quality modifications, taking as example the Valle de Toluca, Salamanca, and San Luis Potosi aquifers in Mexico's highlands. There, elements such as fluoride, arsenic, iron, and manganese have been detected, resulting from the introduction of older groundwater with longer residence times and distinctive chemical composition (regional flows). High concentrations of other elements such as chloride, sulfate, nitrate, and vanadium, as well as pathogens, all related to anthropogenic pollution sources (wastewater infiltration, irrigation return flow, and atmospheric pollutants, among others) were also observed. Some of these elements (nitrate, fluoride, arsenic, iron, and manganese) have shown concentrations above Mexican and World Health Organization drinking water standards.     

Spatial patterns of nitrate,chloride, sulfate,and fluoride concentrations in the Woodbine Aquifer of north-central Texas

A geographic information system was used to map and analyze nitrate, chloride, sulfate, and fluoride concentrations in 110 wells tapping the Woodbine Aquifer. The study area, covering ninecounties in north-central Texas, includes large percentages of both urban and agricultural land uses. Land use maps were compared with solute concentration data, and statistics were applied to detect associations between solutes, well depth, andland use. Anthropogenic sources such as fertilizer applications and natural sources such as gypsum, lignite, and clay deposits controlled nitrate, chloride, and sulfate concentrations, each inversely correlated with well depth. However, only one nitrate observation – from a shallow well in the aquifer's outcrop zone – surpassed the maximum contaminant level (MCL) of 44.3 mg L^-1. By comparison, nearly half of the sulfate and several of the chloride observations surpassed the MCL of 250 mg L^-1for each of those ions. Volcanic ash deposits influenced fluorideconcentrations, which directly correlated with well depth. There were no statistically significant associations between solute concentrations and land use. Low recharge rates and confining layers have mitigated anthropogenic impacts on solute levels in the aquifer.     

Spatial variability of salinity and alkalinity of a field having salination risk in semi-arid climate in northern Turkey

Spatial variability of salinity and alkalinity is important for site-specific management since they are the most important factors influencing soil quality and agricultural production. The objectives of this study were to analyze spatial variability in salinity and alkalinity and some soil properties affecting salinity and alkalinity, using classical statistics and geostatistical methods, in an irrigated field with low-quality irrigation water diverted from drainage canals. A field of 5 da was divided into 10 m x 10 m grids (5 lines in the east-west direction and 10 lines in the north-south direction). The soil samples were collected from three depths (0-30, 30-60 and 60-90 cm) at each grid corner. The variation coefficients of OM and sand contents were higher than other soil properties. OM had the maximum variability, with a mean of 1.63% at 0-30 cm depth and 0.71% at 30-60 cm depth. Significant correlations occurred between ESP, EC and each of Ca, Mg, K and CaCO(3) contents of the soils (p<0.01). Experimental semivariograms were fitted to spherical and gaussian models. All geostatistical range values were greater than 36 m. The soil properties had spatial variability at small distances at 60-90 cm depth. EC was variable within short distances at 30-60 cm depth. The nugget effect of ESP increased with soil depth. Kriged contour maps revealed that soils had a salinisation and alkalisation tendency at 60-90 cm depth based on spatial variance structure of the EC and ESP values. Spatial variability in EC and ESP can depend on ground water level, quality of irrigation water, and textural differences.